\frame{
\frametitle{Graph SLAM guideline} 
\begin{columns} 
    \column[h]{.50\textwidth} 
    {
    \begin{itemize} 
    \item implementation based upon Book "Probabilistic Robotics" by Sebastian Thrun
    \item consistent explanation of the core algorithm
    \item contains utility functions like scanmatching or pose updates
    \end{itemize} 
   }
    \column[h]{.50\textwidth} 
    \includegraphics[width=0.8\textwidth]{ProbabilisticRobotics.jpg} 
  \end{columns} 
}


\frame{
\frametitle{Graph SLAM algorithm explained}

\begin{columns} 
    \column[h]{.50\textwidth} 
    {
    \begin{itemize}
    \item initialize 
	\item linearize
	\begin{itemize}
		\item Pose estimation
		\item integrating measurements
	\end{itemize}
	\item reduce - convoluting features into poses
	\item solve	
	\end{itemize}
    }
    \column[h]{.50\textwidth} 
    \includegraphics[width=1\textwidth]{ALG.png} 
  \end{columns} 
	
}

\frame{
\frametitle{Graph SLAM implementation details} % 
\begin{itemize}
	\item Platform Ubuntu, Coding Language Python
	\item Matrix library numpy and scipy used 
	\item Implemented the algorithm completely from the source
	\item no reasonable pose estimation output yet :(
	\item Hard to Debug scenario (voice only: mathematical complex algorithm with no 		deterministic input in the beginning...and numeric which is number black magic)
	\item Deteministic Input Data by using recorded data (rosbag)
	\item Blackboxtesting of Numerics against Matlab
	%it feels like one step forward, and two steps backward
\end{itemize}
}
